Extending capacity planning by positive lead times and optional overtime, earliness and tardiness for effective master production scheduling

Zobolas, G. I.; Tarantilis, Christos D.; Ioannou, George

doi:10.1080/00207540601008374

Cited by 19 publications

(12 citation statements)

References 22 publications

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“…We assume that materials arrive according to their planned schedules. Since on-time delivery is usually one of the manufacturing objectives for foundry companies [30], we do not consider the inventory holding cost at stages A and order promising before allocation review (B-1) as in some of the previous research [19], [31]. However, we include it at stage B-2 to best utilize the stringent capacity.…”

Section: B Order Fulfillment Modelmentioning

confidence: 99%

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

Chiang¹,

Hsu

2014

IEEE Trans. Semicond. Manufact.

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In today's globalization competition, manufacturing firms are using an order fulfillment system to give available-topromise (ATP) capacity efficiently. An ordinary order fulfillment system will plan capacity based on forecasts and assign ATP quotas to incoming orders. Its basic idea is to enhance capacity utilization and avoid poor customer service. However, in the semiconductor industry, demand is highly volatile, and a maketo-order (MTO) manufacturer often runs the risk of cancelled committed demands. In this research, we propose an integrated order fulfillment model for a MTO semiconductor foundry fab to maximize corporate profit. Specifically, we suggest a periodic allocation review mechanism to reallocate unused ATP quotas. We examine the model performance based on different data sets. Results showed that capacity utilization and profitability are improved substantially with the periodic review mechanism, especially when demand forecast is not reliable.Index Terms-Available-to-promise, linear programming, management information systems, order fulfillment, production management.

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Section: B Order Fulfillment Modelmentioning

confidence: 99%

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

Chiang¹,

Hsu

2014

IEEE Trans. Semicond. Manufact.

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“…Several such genetic algorithm-based approaches have been recently published, which range from single machine scheduling problems [21,34] to parallel machine scheduling problems [23] and master production scheduling problem [40].…”

Section: Previous Workmentioning

confidence: 99%

Job shop scheduling based on earliness and tardiness penalties with due dates and deadlines: an enhanced genetic algorithm

Yang

Sun

Saygin

et al. 2011

Int J Adv Manuf Technol

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This paper studies a job shop scheduling problem with due dates and deadlines in the presence of tardiness and earliness penalties. Due dates are desired completion dates of jobs given by the customer, while deadlines are determined by the manufacturer based on customer due dates. Due dates can be violated at the cost of tardiness, whereas deadlines must be met and cannot be violated. The aforementioned scheduling problem, which is NP-hard, can be formulated with the objective function of minimizing the sum of weighted earliness and weighted tardiness of jobs subject to due dates and deadlines. In order to solve this problem, an enhanced genetic algorithm (EGA) is introduced in this paper. EGA utilizes an operation-based scheme to represent schedules as chromosomes. After the initial population of chromosomes is randomly generated, each chromosome is processed through a three-stage decoder, which first reduces tardiness based on due dates, second ensures deadlines are not violated, and finally reduces earliness based on due dates. After the population size is reached, EGA continues with selection, crossover, and mutation. The proposed algorithm is tested on 180 job shop scheduling problems of varying sizes and its performance is discussed.

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“…The author used linear goal programming techniques in the solution process for the problem along with numerical illustrations to show the applicability of the result as well as the types of analytical outcomes. Zobolas, Tarantilis, and Ioannou (2008) improved the MPS (i.e., master production schedule) for the make-to-order manufacturing systems with excessive demand. An algorithm was presented to incorporate diverse constraints, such as fabrication sequences guided by overtime penalties, earliness, and tardiness for resolving the problem.…”

Section: Introductionmentioning

confidence: 99%

A two-stage multiproduct EMQ-based model with delayed differentiation and overtime option for common part’s fabrication

Chiu

Wang

Chou

et al. 2020

JART

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This study explores the two-stage multiproduct economic manufacturing quantity (EMQ)-based system with delayed product differentiation and overtime option for fabrication of common parts. The classic EMQ model determines optimal lot size under assumptions of steady production rate; however, managers of present-day’s manufacturing firms, operating in a highly competitive global business environment, must constantly seeks ways to strengthen their competitive forces, such strategies include: (i) to increase machine utilization through planning multiproduct fabrication; (ii) to evaluate different production schemes to reduce cost, e.g., a delayed differentiation strategy, when a common intermediate product exists in a multiproduct system, wherein all required common parts are manufactured in stage one and final multi-product are produced in the second stage; and (iii) to reduce the cycle time through implementing an overtime strategy. This study is motivated and intended to address the aforementioned real factors. We use mathematical modeling to depict the problem first, then employ the optimization technique to solve it. Our objectives are to not only decide the optimal replenishing policy, but also to explore the effect and joint influence of the postponement and overtime strategy on the optimal policy, machine utilization, system costs, and relevant cost components in the system. Without this in-depth investigation, various crucial information relating to decision making will still be inaccessible to managers in this field.

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Extending capacity planning by positive lead times and optional overtime, earliness and tardiness for effective master production scheduling

Cited by 19 publications

References 22 publications

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

Job shop scheduling based on earliness and tardiness penalties with due dates and deadlines: an enhanced genetic algorithm

A two-stage multiproduct EMQ-based model with delayed differentiation and overtime option for common part’s fabrication

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